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Services · RNA-Seq · Transcriptomics · Metagenomics

From raw data to published results — complete analysis services

Nine core services covering the complete RNA-Seq, Transcriptomics and Metagenomics workflow — no tools to learn, no pipeline to build.

RNA-Seq & Transcriptomics

Complete RNA-Seq & Transcriptomics
analysis pipeline

From raw FASTQ to publication-ready figures and methods text — we handle the entire RNA-Seq and Transcriptomics workflow.

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Bulk RNA-Seq & Differential Gene Expression Analysis

The core of what we do. DESeq2 v1.42 or edgeR v3.36 for robust Differential Gene Expression Analysis with Benjamini-Hochberg FDR correction. Customisable thresholds. Volcano plots, MA plots, heatmaps, and ranked DEG tables at publication quality.

DESeq2edgeRTranscriptomics

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GO, KEGG & Pathway Enrichment

Functional enrichment using clusterProfiler — GO Biological Process, Molecular Function, Cellular Component, KEGG pathways, and Reactome. Bubble plots, network diagrams, and enrichment dotplots for supplementary figures.

clusterProfilerGO enrichmentKEGG

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Gene Set Enrichment Analysis (GSEA)

Pre-ranked GSEA using fgsea v1.28 against MSigDB Hallmark (v7.5.1), KEGG, GO, and custom gene sets. Enrichment plots, leading-edge analysis, and NES tables — identifies biology that ORA alone misses.

GSEAMSigDBfgsea

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TCGA Validation & Survival Analysis

Validate differential expression findings against The Cancer Genome Atlas using TCGAbiolinks v2.30. Kaplan-Meier survival analysis, expression correlation with clinical outcomes, and pan-cancer comparisons.

TCGATCGAbiolinksSurvival

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QC, Alignment & Quantification

Full upstream pipeline: FastQC, Trimmomatic, MultiQC for QC; STAR v2.7.10 or HISAT2 v2.2.1 for alignment to GRCh38 or GRCm39; featureCounts or RSEM for expression quantification.

STARHISAT2FastQC

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Methods Text & Reproducible Code

Every project includes a publication-ready methods paragraph with correctly cited tool versions, complete R scripts with sessionInfo(), and a reproducible analysis environment.

R scriptsReproducibilityMethods

Metagenomics

NEW SERVICE

Metagenomics & microbiome
analysis services

Comprehensive Metagenomics analysis for microbiome characterisation, taxonomic profiling, functional annotation, and cancer-microbiome interaction studies — including multi-omics integration with RNA-Seq.

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16S rRNA Amplicon MetagenomicsNEW

Amplicon-based Metagenomics for microbiome community profiling. DADA2 or QIIME2 pipeline for ASV/OTU clustering, taxonomic classification against SILVA/Greengenes2, alpha/beta diversity, and differential abundance with DESeq2 or LEfSe. Rarefaction curves, PCoA plots, and taxonomy bar charts.

16S rRNAQIIME2DADA2Metagenomics

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Shotgun MetagenomicsNEW

Whole-genome shotgun Metagenomics for high-resolution microbiome characterisation. Host read removal, QC with KneadData, taxonomic profiling with MetaPhlAn4, functional annotation with HUMAnN3 (KEGG, MetaCyc), and strain-level resolution. Ideal for cancer microbiome and gut-tumour axis studies.

ShotgunMetaPhlAn4HUMAnN3

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Multi-omics Integration (RNA-Seq + Metagenomics)NEW

Integrated analysis combining Metagenomics microbiome data with host RNA-Seq Transcriptomics — correlation between microbial taxa and host gene expression, pathway co-enrichment, and multi-layer visualisation. Relevant for cancer immunotherapy, gut-brain axis, and colorectal cancer.

Multi-omicsIntegrationRNA-Seq

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16S rRNA or Shotgun? — Answer 6 questions and find out instantly

Get a recommended approach based on your research question, sample type, and budget — plus a full pipeline overview and sequencing depth guide. Free, no commitment.

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Process

How it works

Four steps from first contact to publication-ready deliverable — for both RNA-Seq and Metagenomics projects.

Send your data

Upload raw FASTQ files, 16S rRNA amplicons, or a count matrix via secure encrypted portal. Share your experimental design, comparison groups, and specific analysis questions.

Feasibility review

Within 24 hours, Vandana reviews your data for completeness and quality. We confirm the plan — or flag issues honestly before starting. No surprises.

Analysis + review

AI-accelerated pipeline runs end-to-end for RNA-Seq or Metagenomics. Every result is reviewed by our cancer genomics and microbiome specialist before delivery.

Receive results

Day 5 or 7: figures, code, DEG/taxonomic tables, methods text, and interpretation summary. Revisions included. No disappearing after delivery.

FAQ

Common questions

Raw FASTQ files plus a simple metadata table. For RNA-Seq: experimental design, comparison groups, covariates. For Metagenomics: sample metadata, sequencing platform, paired/unpaired. If you only have a count matrix or OTU table, we can work with that too.

We check your data before starting and flag any quality concerns within 24 hours. If issues would compromise the analysis, we tell you honestly rather than producing results that won't survive peer review. We'd rather delay than deliver unreliable results.

Yes. Our methods section is written for manuscript inclusion and cites all tools with appropriate versions and references. It meets reporting standards of major oncology and microbiology journals.

One round of revisions is included in every project. Reviewer-requested changes within the original scope are handled within 2–3 business days at no extra charge.

Yes. For RNA-Seq: GRCh38, GRCm39, mRatBN7.2, GRCz11 as standard. For Metagenomics: human gut, mouse gut, soil, and other environments with appropriate reference databases. Contact us with your species and we'll confirm feasibility.

16S rRNA amplicon sequencing targets the bacterial 16S gene for cost-effective community profiling — great for "who is there" questions. Shotgun Metagenomics sequences all DNA for strain-level resolution and functional annotation — better for "what are they doing" questions. We help you choose the right approach for your study.

Not at all. We regularly re-analyse archived datasets with updated reference genomes and current tools — often with significantly better results than the original analysis. The data is not the problem. The analysis is.